Digital projection-radiographic images are commonly represented as “for-processing” pixel values, which have a well-defined relationship to the detected x-ray energy and are proportional to the x-ray attenuation properties of the object being imaged. This relationship is an important factor when selecting the image processing needed to create the “for-display” image required for optimal viewing on a diagnostic workstation or other display modality.
In dual-energy imaging, two images of the same object are acquired under different x-ray beam conditions, such as beam energy and filtration. These images are proportional to the x-ray transmittance of the object for the differing x-ray spectra. These images can then be decomposed to produce material specific images, such as soft-tissue and bone images.
The most widely used method of decomposition processing is log-weighted subtraction. In log-weighted subtraction, the image data for the high- and low-energy images are transformed to be proportional to the natural logarithm of the x-ray energy detected. The low-energy log image is then multiplied by an appropriate weighting factor and subtracted from the high-energy log image to produce either the bone or soft tissue image depending on the value of the weighting factor.
The log-weighted subtraction process, however, alters the relationship between the resulting material specific decomposition image pixel values and the x-ray attenuation properties of the object, which can be problematic for display image processing algorithms designed for single-acquisition digital projection images in several ways. First, the range of pixel values in the material specific decomposition image may differ significantly between the different images and from the range of pixel values typically obtained with a traditional radiograph. Second, the scaling of pixel values with the attenuation of the object components may differ. Finally, the pixel values in the material specific decomposition images may be additively inverted. These problems all interfere with the ability of “for-display” image processing software to provide a visually compatible set of decomposition images. Therefore, there is a need to provide a method of renormalizing the different material specific decomposition images such that the images are on a common scale and that the pixel values in both images have the same relationship to the x-ray attenuation properties of the materials being imaged.
Further, radiologists are trained to view conventional radiographic images. Although the decomposition images formed from dual-energy imaging provide diagnostically important information, a radiologist may wish to view an image that more closely resembles a conventional radiographic image. Therefore, there is a need to provide a method of forming a visually optimized composite image from the dual-energy image data that can serve as a surrogate for a conventional radiographic image, which avoids the need to expose a patient to additional ionizing radiation. There is also a need to provide a method of renormalizing the composite image such that the composite image pixel values have the same relationship to the material x-ray attenuation properties as the material specific decomposition images in order to facilitate “for-display” image processing of the type used for the material decomposition images.